C. Ganeshkumar, Arokiaraj David and D. Raja Jebasingh
The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were…
Abstract
The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.
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Filipa Pires de Almeida, Rob van Tulder and Suzana B. Rodrigues
Implementing the sustainable development goals (SDGs) has proven a significant challenge for companies. While multinational enterprises (MNEs) have shown a real intention to…
Abstract
Implementing the sustainable development goals (SDGs) has proven a significant challenge for companies. While multinational enterprises (MNEs) have shown a real intention to contribute to these goals, they face major barriers in implementing the SDGs in their core business strategies. Extant academic studies on this phenomenon have primarily explored why companies “should” address the SDG agenda but have not (yet) explored what “works,” what does not “work,” and why. Therefore, evidence of a sizable gap between intention and realization is growing. Besides, there is a limited explanation for the existence of this gap and no validated implementation models that could help overcome it. Additionally, management research remains relatively fragmented. The diversity of existing theoretical and empirical frameworks makes it difficult to consolidate scientific and practical insights on “how” to guide companies to accelerate the global goals through their core operations.
This study is one of the first attempts to draw lessons from extant research on effective SDGs’ implementation strategies. For that, we upgrade the “SDG Compass,” which has been recognized as a leading framework for SDGs implementation in companies’ core activities. A critical assessment of the literature on the SDGs implementation has been conducted through a systematic literature review (SLR) and bibliometric analysis. This has helped us identify gaps in the SDG implementation practice and accumulate relevant insights supporting a more integrated and upgraded implementation framework: the SDG Compass+. This framework can advance coordinated theoretical and practical research by identifying the antecedents and critical factors of impactful SDG implementation strategies.
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Varimna Singh, Preyal Sanghavi and Nishant Agrawal
Industry 4.0 (I4.0), the Fourth Industrial Revolution, integrates Big Data analytics, blockchain, cloud computing, digitisation and the Internet of Things to enhance supply chain…
Abstract
Industry 4.0 (I4.0), the Fourth Industrial Revolution, integrates Big Data analytics, blockchain, cloud computing, digitisation and the Internet of Things to enhance supply chain (SC) activities and achieve sustainable growth through dynamic capabilities (DCs). This approach equips businesses with the necessary tools to optimise their operations and remain competitive in a dynamic business environment. The value proposition of a business encompasses a wide range of activities that add value at each stage. By leveraging DCs, a firm can achieve innovation, gain a competitive advantage and enhance its adaptability. Conversely, effective value chain management can amplify the influence of a firm's DCs on SC sustainability, by reducing waste, optimising resource utilisation and fostering strategic partnerships. This mutually beneficial connection takes the form of a dynamic interaction in which I4.0 technologies act as a catalyst to help organisations become more resilient, adaptive and responsive. The adoption of these technologies denotes a comprehensive approach to business shift, not merely technical integration. I4.0 has an impact on several organisational disciplines outside of manufacturing, from automation and efficiency advantages to quality enhancements. This chapter offers an extensive literature review to explore the level of SC sustainability that a business can achieve by combining its DCs and implementing strategic I4.0 adoption. The function of value chain management in moderating the effects of I4.0 and DCs on SC sustainability is also assessed. This study proposes a theoretical model that is grounded in the insights extracted from the literature review.
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Narender Kumar, Girish Kumar and Rajesh Kr Singh
The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study…
Abstract
Purpose
The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.
Design/methodology/approach
The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.
Findings
The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.
Practical implications
This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.
Originality/value
The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.
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The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of…
Abstract
Purpose
The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of non-Newtonian nanofluid flows between two porous parallel plates in the presence of Lorentz force are taken into account in this research.
Design/methodology/approach
The governing partial differential equations (PDEs) were nondimensionalized using suitable nondimensional quantities to transform the PDEs into a system of coupled nonlinear PDEs. The resulting equations are solved using the spectral relaxation method due to the effectiveness and accuracy of the method. The obtained velocity and temperature profiles are used to compute the entropy generation rate and Bejan number. The influence of various flow parameters on the velocity, temperature, entropy generation rate and Bejan number are discussed graphically.
Findings
The results indicate that the energy losses can be minimized in the system by choosing appropriate values for pertinent parameters; when thermal conductivity is increasing, this leads to the depreciation of entropy generation, and while this increment in thermal conductivity appreciates the Bejan number, the Eckert number on entropy generation and Bejan number, the graph shows that each time of increase in Eckert will lead to rising of entropy generation while this increase shows a reduction in Bejan number. To shed more light, these results were further demonstrated graphically. The current research was very well supported by prior literature works.
Originality/value
All results are presented graphically, and the results in this article are anticipated to be helpful in the area of engineering.
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Kalpna Guleria and Anil Kumar Verma
Wireless sensor networks (WSNs) have emerged as one of the most promising technology in our day-to-day life. Limited network lifetime and higher energy consumption are two most…
Abstract
Purpose
Wireless sensor networks (WSNs) have emerged as one of the most promising technology in our day-to-day life. Limited network lifetime and higher energy consumption are two most critical issues in WSNs. The purpose of this paper is to propose an energy-efficient load balanced cluster-based routing protocol using ant colony optimization (LB-CR-ACO) which ultimately results in enhancement of the network lifetime of WSNs.
Design/methodology/approach
The proposed protocol performs optimal clustering based on cluster head selection weighing function which leads to novel cluster head selection. The cluster formation uses various parameters which are remaining energy of the nodes, received signal strength indicator (RSSI), node density and number of load-balanced node connections. Priority weights are also assigned among these metrics. The cluster head with the highest probability will be selected as an optimal cluster head for a particular round. LB-CR-ACO also performs a dynamic selection of optimal cluster head periodically which conserves energy, thereby using network resources in an efficient and balanced manner. ACO is used in steady state phase for multi-hop data transfer.
Findings
It has been observed through simulation that LB-CR-ACO protocol exhibits better performance for network lifetime in sparse, medium and dense WSN deployments than its peer protocols.
Originality/value
The proposed paper provides a unique energy-efficient LB-CR-ACO for WSNs. LB-CR-ACO performs novel cluster head selection using optimal clustering and multi-hop routing which utilizes ACO. The proposed work results in achieving higher network lifetime than its peer protocols.
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Monireh Panbehkar-Jouybari, Mehdi Mollahosseini, Asieh Panjeshahin and Mahdieh Hosseinzadeh
Garlic supplementation may be inversely contributed to body weight and composition; however, previous results have been inconsistent. This study aims to evaluate the effect of…
Abstract
Purpose
Garlic supplementation may be inversely contributed to body weight and composition; however, previous results have been inconsistent. This study aims to evaluate the effect of garlic supplementation on body weight and composition using a systematic review and meta-analysis.
Design/methodology/approach
Online databases of PubMed, ISI Web of Science, Scopus and Google Scholar were searched up to January 2020. The random-effects model was used to calculate the effect sizes of the included studies. The risk of bias of included studies was assessed using the Cochrane collaboration’s tool. Besides, the NutriGrade scoring system was applied to judge the credibility of the evidence.
Findings
In total, 18 studies (with 1,250 participants) were included in the meta-analysis. The pooled analysis revealed that garlic supplementation has a significant increase in body weight [weighted mean difference (WMD) = 0.31 Kg, 95% CI: 0.09, 0.53 Kg, P = 0.005, n = 12 effect sizes]. Waist circumference (WC) does remarkably reduce [WMD = −1.28 cm, 95% CI: −2.08, −0.47 cm, P = 0.002, n = 4 effect size]. However, body mass index, body fat percent and fat-free mass do not dramatically change (P > 0.05). Notably, the pooled analyses on body weight and WC were sensitive to two included studies. NutriGrade’s score was rated low for this meta-analysis.
Originality/value
Although garlic supplementation could slightly increase weight and simultaneously might decrease WC, these associations were not strong enough to corroborate the findings. Also, other anthropometric indices do not significantly change. Further well-designed randomized clinical trial studies are needed to confirm the results.
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Brigitte Wecker and Matthias Brauer
Misconduct allegations have been found to not only affect the alleged firm but also other, unalleged firms in form of reputational and financial spillover effects. It has remained…
Abstract
Misconduct allegations have been found to not only affect the alleged firm but also other, unalleged firms in form of reputational and financial spillover effects. It has remained unexplored, however, how the number of prior allegations against other firms matters for an individual firm currently facing an allegation. Building on behavioral decision theory, we argue that the relationship between allegation prevalence among other firms and investor reaction to a focal allegation is inverted U-shaped. The inverted U-shaped effect is theorized to emerge from the combination of two effects: In the absence of prior allegations against other firms, investors fail to anticipate the focal allegation, and hence react particularly negatively (“anticipation effect”). In the case of many prior allegations against other firms, investors also react particularly negatively because investors perceive the focal allegation as more warranted (“evaluation effect”). The multi-industry, empirical analysis of 8,802 misconduct allegations against US firms between 2007 and 2017 provides support for our predicted, inverted U-shaped effect. Our study complements recent misconduct research on spillover effects by highlighting that not only a current allegation against an individual firm can “contaminate” other, unalleged firms but that also prior allegations against other firms can “contaminate” investor reaction to a focal allegation against an individual firm.
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Vikas Kumar, Banu Yetkin Ekren, Jiayan Wang, Bhavin Shah and Guilherme Francisco Frederico
The ongoing pandemic has gravely affected different facets of society and economic trades worldwide. During the outbreak, most manufacturing and service sectors were closed across…
Abstract
Purpose
The ongoing pandemic has gravely affected different facets of society and economic trades worldwide. During the outbreak, most manufacturing and service sectors were closed across the globe except for essential commodities such as food and medicines. Consequently, recent literature has focused on studying supply chain resilience and sustainability in different pandemic contexts. This study aims to add to the existing literature by exploring the economic, environmental and societal aspects affecting the food supply chain and assessing the impact of COVID-19 on food sustainability.
Design/methodology/approach
A survey method has been adopted with a questionnaire instrument investigating the role of technology, government policies, geopolitics and intermediaries on sustainable organisational management. A five-point Likert scale (i.e. 1 = strongly disagree; 5 = strongly agree) is used to evaluate the responses. The findings are based on 131 responses from entry-level workers and senior executives of different food supply chains across Asia and Europe. The data has been analysed to derive insights into the impacts of this pandemic.
Findings
The survey concludes with the significant impact of COVID-19 on the three pillars of sustainability, i.e. economic, social and environmental dimensions. The empirical analysis shows digitalisation and its applications help mitigate the negative effect of COVID-19 on sustainability. In addition, the supportive government policies and intermediatory interventions were helpful in improving sustainability at each level.
Research limitations/implications
The findings have implications for businesses and policymakers. Companies can learn from the advantages of digitalisation to counter the challenges imposed by the pandemic or similar situations in the future in maintaining the sustainability of their supply chains. Managers can also learn the importance of effective organisational management in driving sustainability. Finally, policymakers can devise policies to support businesses in adopting sustainable practices in their supply chains.
Originality/value
This study adds to the limited literature exploring the impact of COVID-19 on food supply chain sustainability through the triple bottom line lens. To the best of the authors’ knowledge, this is also one of the first empirical studies to examine the effect of technology, government and organisational management practices on the sustainability of food supply chains.
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Vinay C.A. and Kumar G.N.
Development or upgradation of airplanes requires many different analyses, e.g. thermal, aerodynamic, structural and safety. Similar studies were performed during configuration…
Abstract
Purpose
Development or upgradation of airplanes requires many different analyses, e.g. thermal, aerodynamic, structural and safety. Similar studies were performed during configuration change design of commuter category aircraft equipped with pusher turboprop engines. In this paper, thermo-fluid analyses of interactions of the new propulsion system in tractor configuration with selected elements of airplane skin are carried out. This study aims to check the airplane skin material, and its geometry, including the Plexiglas passenger window material degradation, due to hot exhaust gas plume impingement. The impact of change in exhaust stub angle and asymmetric inboard-outboard stubs on the jet thrust at various flight operating conditions like minimum off-route altitude and cruise performance is assessed.
Design/methodology/approach
Commercial software-based numerical models were developed. In the first stage, heat and fluid flow analysis was performed over a twin-engine airplane’s nacelle, wing and center fuselage with its powerplant mounted in the high wing configuration. Subsequently, numerical simulations of thermal interactions between the hot exhaust gases, which leave the exhaust system close to the nacelle, flaps and the center fuselage, were estimated for various combinations of exhaust stub angles with asymmetry between inboard-outboard stubs at different airplane configurations and operating conditions.
Findings
The results of the simulations are used to recommend modifications to the design of the considered airplane in terms of material selection and/or special coatings. The importance and impact of exhaust jet thrust on the overall aircraft performance are investigated.
Originality/value
The advanced numerical model for the exhaust jet-airplane skin thermal interaction was developed to estimate the temperature effects on the propeller blades and aircraft fuselage surfaces during different flight operating conditions with multiple combinations of stub orientations.